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The research proposes a model to estimate the carbon stock in mangrove forests from multispectral images from Landsat 8 and Sentinel 2B satellites. The Gramame River mangrove, located on the southern coast of Paraíba State, Brazil, was adopted as the study area. Carbon stocks in biomass, below and above ground, were measured from a forest inventory, and vegetation indices were processed on the Google Earth Engine (GEE) platform. To define the fit curves, linear and non-linear regressions were used. The choice of the model considered the highest coefficients of determination (R 2 ), the biomass and carbon stock were estimated from the equations. The biomass carbon stock, calculated from field data, corresponded to 22.27 Gg C, equivalent to 81.75 Gg CO 2 , with 13.85 Gg C (50.84 Gg CO 2 ) and 8.42 Gg C (30.91 Gg CO 2 ) stored in biomass above and below ground, respectively. Among the models fitted to the indices calculated from Landsat 8 images, NDVI was the one that best explained the spatial distribution of biomass and carbon, with 90.26%. For Sentinel 2B, SAVI was able to explain 80.76%. The total estimated plant carbon stocks corresponded to 26.66 Gg (16.20 Gg C above and 10.36 Gg C below ground) for Landsat 8 and 27.76 Gg C (16.93 Gg C above and 10.83 Gg C below ground) for Sentinel 2B. The proposed work methodology and the suggested mathematical models can be replicated to analyze carbon stocks in other locations, especially in the Americas, because they share the same species., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The development of an environment that is sustainable requires infrastructure matching this goal. Moreover, it is almost impossible to achieve this goal without the requisite energy structure. Devising an energy structure that is both effective and efficient must precede the desired infrastructure to achieve sustainability goals. Therefore, it is important to look into the nexus of energy structure, infrastructure, and carbon emissions in "Brazil, Russia, India, China, and South Africa (BRICS)" countries under the growth and environment hypothesis. To empirically estimate the said nexus, robust econometric techniques are adopted. This paper employs panel data analysis techniques to investigate the relationship between infrastructure, energy consumption, and carbon emissions in the BRICS countries. The econometric estimation methodology includes a cross-sectional dependence test, unit root attribute of the panel data using the cross-sectionally augmented Im Pesaran and Shin (CIPS) test, and estimation of co-integration among the variables, and to address the issues in the panel data, augmented mean group (AMG) technique and common correlated effects mean group (CCEMG) estimator were employed. Findings suggest the existence of a supportive role of infrastructure and energy structure in abating carbon emissions. It is suggested that the BRICS economies need to enhance their investment in infrastructure and energy structure for them to create a sustainable environment. Findings are also robust to short- and long-run policy implications. This study is a step forward toward the Sustainable Development Goals (SDGs)., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The study was aimed at investigating the dynamic relationship between environmental taxes, green financing, and carbon dioxide (CO 2 ) emissions in Brazil, China, India, and South Africa from 1994 to 2019. To thoroughly examine the proposed relationship, a family of robust econometric methods is used to get reliable and accurate results. Our evidence indicates that green finance and CO 2 emissions are negatively connected with each other. Similarly, positive relationship is found between environmental taxes and CO 2 emissions. Additionally, environmental taxes and green finance are positively related as well. Further, the results of the Method of Moments Quantile Regression estimator indicate that green finance and CO 2 emissions decrease in countries with higher pollution compared to those with lower pollution. Interestingly, environmental taxes only contribute to pollution in countries with higher emissions, whereas CO 2 emissions increase environmental taxes in all sample countries. Lastly, green finance has a mitigating effect only in countries with greater pollution, and CO 2 emissions have a negative rebound effect on green finance in countries with greater CO 2 emissions. According to the evidence, green financing can be an effective tool for promoting environmental quality. By allocating the funds collected from environmental taxes to green financing, environmental sustainability can be promoted in sample countries., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Environmental sustainability concerns are growing worldwide. Many recent studies have focused on key indicators of CO2 emissions, but less consideration has been given to human capital. This study examines the impact of human capital on CO2 emissions in Brazil, Russia, India, China, and South Africa (BRICS) economies from 1991 to 2019 using a nonlinear panel autoregressive distributed lag approach. Findings show that positive change in education has reduced CO2 emissions, while a negative change in education has increased CO2 emissions in the long run in a group of BRICS. Regarding economy-wise analysis, a positive change in education reduces CO2 emissions in Russia, China, and South Africa in the long run, but a negative change in education has an increasing impact on CO2 emissions in Brazil and China. The results of robustness are also maintained in group and economy-wise empirical analysis. Policymakers should develop the education sector infrastructure in order to support the decrease of CO2 emissions., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In this paper, we use (Yilanci et al. 2020) Fourier autoregressive distributed lag (ARDL) model to study the correlation between health expenditures, CO 2 emissions, and GDP fluctuations in BRICS countries from 2000 to 2019. The Fourier ARDL model has the function of bootstrap repeated simulation calculations, so that small samples can also achieve the advantages of finer inspection results. In this paper, we find that in the long term, Brazil and China are countries that both have cointegration relationships in health expenditure, CO 2 emissions, and economic growth. With CO 2 emissions as the dependent variable and health expenditure and economic growth as independent variables, in the short term, there is a negative causal relationship between India's CO 2 emissions and health expenditure; other countries only show the relationship between CO 2 emissions, health expenditure, or economic growth one-way relationship. This paper also has some policy suggestions on health expenditures and CO 2 emissions in the BRICS countries at the end., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study investigates the effect of financial development and economic growth on ecological footprint by including non-renewable energy consumption and trade openness as additional determinants. For this purpose, annual data of 10 countries with the highest ecological footprint (China, the USA, India, Japan, Brazil, Indonesia, Mexico, Korea, Turkey, and the UK) for the period 1992-2017 is used. The Westerlund and Edgerton (2007) Panel LM bootstrap test results reveal that there is cointegration between the variables. Additionally, the results obtained from the Common Correlated Effects (CCE) coefficient estimator show that financial development, economic growth, and non-renewable energy consumption negatively affect environmental quality by increasing ecological footprint. On other hand, the effect of trade openness on ecological footprint is found to be statistically insignificant. In addition, according to the panel causality test results, a unidirectional causality from financial development to ecological footprint is found while bidirectional causality between economic growth and ecological footprint exists. Therefore, it would be beneficial for policymakers in such countries to direct financial resources to green energy production and consumption and to encourage projects and practices., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

With rapid economic growth, BRICS is facing enormous burdens of carbon emission and severe issues of income inequality. However, behind this economic success, the BRICS economies also face few thoughtful challenges to improve environmental quality by catching up the sustainable development goals. Consequently, the existing empirical research is concerned with the dynamic links between income inequality and CO 2 emissions by using the novel nonlinear ARDL approach, but small attention has been paid to the BRICS in literature. Therefore, we observed that a negative and positive change in income inequality has positive effect on CO 2 emissions in Russia and South Africa in the long run, although a positive change in income inequality has positive effects on CO 2 emissions in Brazil, Russia, and China, while a negative change in income inequality has negative effect on CO 2 emissions in India, Brazil, and Russia in the short run. Hence, the findings value specific attention from policymakers in BRICS economies., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Soil CO 2 emission (FCO 2 ) is a critical component of the global carbon cycle, but it is a source of great uncertainty due to the great spatial and temporal variability. Modeling of soil respiration can strongly contribute to reducing the uncertainties associated with the sources and sinks of carbon in the soil. In this study, we compared five machine learning (ML) models to predict the spatiotemporal variability of FCO 2 in three reforested areas: eucalyptus (RE), pine (RP) and native species (RNS). The study also included a generalized scenario (GS) where all the data from RE, RP and RNS were included in one dataset. The ML models include generalized regression neural network (GRNN), radial basis function neural network (RBFNN), multilayer perceptron neural network (MLPNN), adaptive neuro-fuzzy inference system (ANFIS) and random forest (RF). Initially, we had 32 attributes and after pre-processing, including Pearson's correlation, canonical correlation analysis (CCA), and biophysical justification, only 21 variables remained. We used as input variables 19 soil properties and climate variables in reforested areas of eucalyptus, pine and native species. RF was the best model to predict soil respiration to RE [adjusted coefficient of determination (R 2 adj): 0.70 and root mean square error (RMSE): 1.02 µmol m -2  s -1 ], RP (R 2 adj: 0.48 and RMSE: 1.07 µmol m -2  s -1 ) and GS (R 2 adj: 0.70 and RMSE: 1.05 µmol m -2  s -1 ). Our findings support that RF and GRNN are promising for predicting soil respiration of reforested areas which could help to identify and monitor potential sources and sinks of the main additional greenhouse gas over ecosystems., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The urgent global climate change situation forces the steel industry to confront enormous challenges and complex tasks. This research focuses on the steel sector and incorporates data from 56 nations between 2010 and 2018. We analyze the direct and indirect effects of the steel trade on CO 2 emissions using the spatial Durbin model. The results show that Moran's I ranges from 0.414 to 0.521, suggesting that carbon emissions are very spatially dependent. Developed countries such as Japan, Germany, and the USA form high-high agglomeration areas. In contrast, Brazil, Thailand, and India constitute low-low agglomeration areas. Under the three spatial weight matrices, the direct effect coefficients of steel exports are 0.045, 0.038, and 0.057, and the indirect effect coefficients are - 0.006, - 0.076, and - 0.015, indicating that steel exports increase local CO 2 emissions while decreasing carbon emissions in neighboring countries. Urbanization and per capita GDP have positive spatial spillover effects, while the spatial effect of R&D intensity is insignificant. Increased industrialization and renewable energy consumption positively affect carbon emission reduction in local and surrounding nations. The study provides empirical evidence for the steel industry to develop emission reduction strategies., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Since energy is one of the basic inputs for development, emerging economies should make an effort to investigate the environmental impacts of their fast economic growth. However, large emerging economies present significant regional heterogeneity that is usually uncounted for. This study uses the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model and regional data on the 27 Brazilian states to investigate the growth-CO 2 nexus under distinct development stages. To perform this analysis, we divided the states into three groups according to their average annual GDP (i.e., richer, intermediate, and poorer regions). The results suggest that richer and poorer regions, particularly, present economic and demographic developments that are environmentally costly. Also, population and per capita GDP have the largest influences on CO 2 emissions. The roles of the industrial sector and the ascending service sector are also subject to criticism. Moreover, Brazil arguably suffers from technological stagnation as its energy intensity is growing and boosting CO 2 emissions. We discuss the policy implications of these findings and suggest a future research agenda., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study examines the gasification kinetics of Brazilian municipal solid waste (MSW) and its components under air, CO 2, and air/CO 2 (70/30 vol%) atmospheres. The ignition indices of paper and plastic are 6 and 3 times that of food waste, which are 38.6 × 10 -3  %/min 3 and 19.6 × 10 -3  %/min 3 , respectively, implying a faster separation of volatile compounds from the paper and plastic. The minimum E α values of 132 kJ/mol and 140 kJ/mol have been obtained for paper waste under air and air/CO 2 , respectively. On CO 2 condition, MSW has an average E a value of 96 kJ/mol. Under an air/CO 2 atmosphere, a high synergistic ΔW of -4.7 wt% has been identified between individual components. The presence of air and CO 2 improves the oxidation and char gasification process, thus resulting in better combustion. Hence, the gasification of MSW under an air/CO 2 atmosphere would improve the waste-to-energy plant's performance and minimize the CO 2 emission., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Mangroves forests may be important sinks of carbon in coastal areas but upon their death, these forests may become net sources of carbon dioxide (CO 2 ) and methane (CH 4 ) to the atmosphere. Here we assessed the spatial and temporal variability in soil CO 2 and CH 4 fluxes from dead mangrove forests and paired intact sites in SE-Brazil. Our findings demonstrated that during warmer and drier conditions, CO 2 soil flux was 183 % higher in live mangrove forests when compared to the dead mangrove forests. Soil CH 4 emissions in live forests were > 1.4-fold higher than the global mangrove average. During the wet season, soil GHG emissions dropped significantly at all sites. During warmer conditions, mangroves were net sources of GHG, with a potential warming effect (GWP100) of 32.9 ± 10.2 (±SE) Mg CO 2 e ha -1 y -1 . Overall, we found that dead mangroves did not release great amounts of GHG after three years of forest loss., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The conversion of native vegetation to agricultural areas leads to a natural process of carbon loss but these systems can stabilize in terms of carbon dynamics depending on the management and conversion time, presenting potential to both store and stabilize this carbon in the soil, resulting in lower soil respiration rates. In this context, this study aimed to investigate the effect of converting native Cerrado forest areas to agricultural systems with a forest planted with Eucalyptus camaldulensis and silvopastoral systems on the dynamics of CO 2 emission and carbon stock at different soil depths. The experimental sites are located in the Midwest of Brazil, in the coordinates 20°22'31″ S and 51°24'12″ W. Were evaluated soil CO 2 emission (FCO 2 ), soil organic carbon, the degree of humification of soil organic matter (HLIFS), soil temperature, soil moisture, and soil chemical and physical attributes. The soil of the area is classified as an Oxisol (Haplic Acrustox). Soil samples were collected at depths of 0.00-0.10, 0.10-0.20, 0.20-0.30, and 0.30-0.40 m. The lowest FCO 2 values were found in the silvopastoral system (1.05 μmol m -2  s -1 ), followed by the native forest (1.65 μmol m -2  s -1 ) and the eucalyptus system (1.96 μmol m -2  s -1 ), indicating a 36% reduction in FCO 2 compared to the conversion of the native forest to the silvopastoral system and an increase of 19% when converting the native forest to the eucalyptus system. The soil chemical attributes (N, K + , Ca 2+ , H + +Al 3+ , CEC, and organic carbon) showed a decrease along the profile. The shallowest depths (0.00-0.10 and 0.10-0.20 m) presented no differences between systems but the subsequent depths (0.20-0.30 and 0.30-0.40 m) had a difference (95% confidence interval), relative to N, Ca 2+ , H + +Al 3 , CEC, and organic carbon stock (OCS), and the soil under silvopastoral system showed a higher concentration of these attributes than the native forest. The multivariate analysis showed that the eucalyptus and silvopastoral systems did not differ from the forest in the shallowest soil layer but differed from each other. This behavior changed from the second assessed depth (0.10-0.20 m), in which the silvopastoral system stands out, differing both from the eucalyptus system and from the native forest, and this behavior is maintained at the following depths (0.20-0.30 and 0.30-0.40 m). OCS, H + +Al 3 , CEC, and nitrogen are strongly related to land use change for silvopastoral system. Regarding the behavior/relationship of attributes as a function of depth, the silvopastoral system contributed to soil carbon accumulation and stability over consecutive years., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Hop cultivation has been increasing in the past decade in Brazil, demanding a better understanding of how the processing influences the national hop varieties. Despite the hop process being well-established in the producer countries, there is still room for optimization to reduce energy consumption for a more sustainable process. This study's main purpose was to understand the influence of drying and supercritical CO 2 extraction on the quality of hop extracts. The hop quality during drying was evaluated regarding color, bitter acids, xanthohumol, total essential oil content, and volatile profile. Supercritical CO 2 extraction yields, and bitter acid recovery were assessed by HPLC in a range of different temperatures (40 or 60 °C) and pressure (15, 20, 25, or 30 MPa) conditions. Hop processing was optimized to produce a greater extract quality from a Brazilian hop variety, saving energy and solvent consumption, and consequently, reducing the process footprint. Furthermore, this study established supercritical CO 2 extraction conditions for Brazilian hop extract production, offering the national beer industry an alternative to overpriced products., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Studies have shown that energy consumption from economic development leads to an increase in carbon emissions. Emerging economies, as important sources of carbon emissions with high growth potential, play a crucial role in global decarbonisation efforts. However, the spatial pattern and evolution trend of carbon emissions in emerging economies have not been studied in depth. Therefore, this paper uses the improved gravitational model and carbon emission data from 2000 to 2018 to construct a spatial correlation network of carbon emissions in 30 emerging economies around the world, aiming to reveal the spatial characteristics and influencing factors of carbon emissions at the national level. The results show that the spatial network structure of carbon emissions in emerging economies is closely linked, forming a "big network" of interconnection. Amongst them, Argentina, Brazil, Russia, Estonia, etc. are at the centre of the network and play a leading role. Geographical distance, economic development level, population density, and scientific and technological level have a significant impact on the formation of spatial correlation between carbon emissions. Further use of GeoDetector shows that the explanatory power of two-factor interaction on centrality is greater than that of a single factor, indicating that a single economic development cannot well enhance the influence of countries in the carbon emission network, and needs to be combined with factors such as industrial structure and scientific and technological level. These results are helpful to understand the correlation between carbon emissions between countries from the perspective of the whole and part and provide a reference for optimizing the carbon emission network structure in the future., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The emission of soil carbon dioxide (CO 2 ) in agricultural areas is a process that results from the interaction of several factors such as climate, soil, and land management practices. Agricultural practices directly affect the carbon dynamics between the soil and atmosphere. Herein, we evaluated the temporal variability (2020/2021 crop season) of soil CO 2 emissions and its relationship with related variables, such as the CO 2 flux model, enhanced vegetation index (EVI), gross primary productivity (GPP), and leaf area index (LAI) from orbital data and soil temperature, soil moisture, and soil CO 2 emissions from in situ collections from native forests, productive pastures, degraded pastures, and areas of high-yield potential soybean and low-yield potential soybean production. A significant influence (p < 0.01) was observed for all variables and between the different land uses and occupation types. September and October had lower emissions of soil CO 2 and low means of soil moisture and soil temperature, and no differences were observed among the treatments. On the other hand, there was a significant effect of the CO 2 flux model in productive pastures, high-yield potential soybean areas, and low-yield potential soybean areas. The months with the highest CO 2 flux values in the model, regardless of land use and land cover, were October and November, which is the beginning of the rainy season. There were positive correlations between soil CO 2 emissions and GPP (0.208), LAI (0.354), EVI (0.363), and soil moisture (0.280) and negative correlations between soil CO 2 emissions and soil temperature (-0.240) and CO 2 flux model (-0.314) values. Land use and land cover showed negative correlations with these variables, except for the CO 2 flux model variable. Soil CO 2 emission values were lower for high-yield potential soybean areas (averages from 0.834 to 6.835 μmol m -2 s -1 ) and low-yield potential soybean areas (from 0.943 to 5.686 μmol m -2 s -1 ) and higher for native forests (from 2.279 to 8.131 μmol m -2 s -1 ), whereas the opposite was true for the CO 2 flux model., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

In this paper, the effects of economic growth and four different types of energy consumption (oil, natural gas, hydroelectricity, and renewable energy) on environmental quality in terms of carbon dioxide (CO 2 ) emissions were examined within the framework of the Environmental Kuznets Curve (EKC) for three Latin American countries, namely, Argentina, Brazil, and Chile, from 1975 to 2018. The autoregressive distributed lag (ARDL) in the form of Error Correction Mechanism (ECM) was used to verify the validity of the EKC hypothesis and the impacts of the variables in the short and the long run alike. Furthermore, the Toda-Yamamoto Granger causality test was carried out to identify the direction of causality between the variables. From ARDL-ECM estimation, the EKC was confirmed (inverted U-shaped curve between income growth and CO 2 emissions) only in Argentina in the long run but not in Brazil and Chile. Based on the findings, renewable energy can have a great potential in reducing CO 2 emissions in the future, but this advantage has not been fully exploited yet since a significant negative impact on CO 2 emissions was only found in Chile. Also, the use of other less carbon-intensive energy sources such as natural gas and hydropower if they could be combined with renewable energy would be of great benefit and contribute to enhancing environmental quality and energy security in the short and the medium term and to successful low-carbon energy transition in the long run in Argentina, Brazil, and Chile., (© 2022. The Author(s).)

The concept of environmental sustainability formed the basis of the Paris Agreement and the United Nations conference in Rio de Janeiro. Empirically, without environmental sustainability, everything else could fall apart or be aimless. This study investigates factors affecting global environmental sustainability spanning 1966Q1 to 2019Q4. However, there are many micro-/macroeconomic factors engendering the environment, and the absence of robust clarity on whether factors such as economic growth, urbanization, trade openness, and energy consumption matter for global environmental sustainability remains a global academic dilemma in the economics literature. This paper utilized the unrestricted nonlinear autoregressive distributed lag (NARDL) bounds test techniques to model their relationship. Furthermore, the study adopted fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and canonical cointegrating regression (CCR) methods to test the research hypothesis, catering to the problem of endogeneity and serial correlation. Up-to-date of this study, no empirical study has examined the nexus of these variables within the global framework. The outcomes suggested that (i) NARDL bounds test of cointegration confirmed evidence of long-run and short-run relationships among the variables; (ii) long-run asymmetric relationship was affirmed among the variables; and (iii) DOLS, FMOLS, and CCR models demonstrate that economic growth, energy consumption, and trade openness are positively significantly correlated with environmental sustainability except for economic growth which shows negative and insignificant correlation. These findings validate the protracted argument in literature that these estimated variables are significant for global environmental sustainability. This study recommends that environmental policymakers integrate global economic incentives with favorable regulatory changes for achieving the goals of a global sustainable environment in the long-run equilibrium., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Flexible pipes are modular constructions made up of several layers. They are broadly employed in oil & gas industry, playing an important role in the Brazilian Pre-Salt production. Under specific conditions, seawater can ingress and this contact with metallic middle layers can significantly lead to a service life reduction of these layers, especially due to a mechanism known as CO 2 Stress Corrosion Cracking (SCC-CO 2 ). Therefore, it becomes mandatory that inspection systems suitable for submarine use in order to detect annulus flooding before the failure of the flexible pipe become available. This paper presents an inspection system based on the gamma rays transmission focused on detecting such flood condition, possibly overcoming limitations of other inspection systems available in the market. The reliability of this solution was statistically evaluated as presented herein, showing great robustness based on the numerous available trials., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This paper scrutinizes the asymmetric impact of education and education expenditure on clean energy consumption and CO2 emissions in the BRICS economies using annual data for the period 1991-2019. The analysis employs a nonlinear autoregressive distributed lag (ARDL) framework. Findings unfold that a positive change in education contributes to increasing clean energy consumption in Brazil, Russia, India, and China. This finding implies that a negative change in education contributes to reducing clean energy consumption in Brazil, Russia, and India in the long run. Nonetheless, a positive change in education expenditure increased the clean energy consumption in Brazil, Russia, and India, while it has decreased in South Africa. On the dark side, a negative change in education expenditure degrades clean energy consumption in India, China, and South Africa in the long run. The asymmetric empirical results of CO2 emissions are mixed, economy-specific, and vary across group countries in the long run. We find that the education and education expenditure has long-run asymmetric effects in BRICS industries. Thus empirical findings give us robust policy implications for BRICS economies., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The role of government size and digitization in the process of environmental quality is a matter of considerable debate in the field of environmental economics. BRICS economies have suffered from environmental pollution. This paper scrutinizes that how CO 2 emissions respond to government size and digitization in BRICS economies. Empirical estimates of the ARDL approach show that government size has a positive impact on CO 2 in Brazil, India, and China, while negative impact on CO 2 in Russia in the long run. The long-run estimates reveal a negative and significant effect of digitization on CO 2 in Brazil, India, and China. Education and e-learning activities have a favorable and crucial role played in environmental quality in Brazil, India, and China. Based on these findings, BRICS authorities should improve the efficiency of government expenditures and invest more in digitization to improve the quality of the environment., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Ocean Alkalinity Enhancement (OAE) has recently gained attention as a potential method for negative emissions at gigatonne scale, with near-coast OAE operations being economically favorable due to proximity to mineral and energy sources. In this paper we study critical questions which determine the scale and viability of OAE: Which coastal locations are able to sustain a large flux of alkalinity at minimal pH and ΩArag (aragonite saturation) changes? What is the interference distance between adjacent OAE projects? How much CO2 is absorbed per unit of alkalinity added? How quickly does the induced CO2 deficiency equilibrate with the atmosphere? Using the LLC270 (0.3deg) ECCO global circulation model we find that the steady-state OAE rate varies over 1–2 orders of magnitude between different coasts and exhibits complex patterns and non-local dependencies which vary from region to region. In general, OAE in areas of strong coastal currents allow the largest fluxes and depending on the direction of coastal currents, neighboring OAE sites can exhibit dependencies as far as 400 km or more. We found that within relatively conservative constraints set on ∆pH or ∆Omega, most regional stretches of coastline are able to accommodate on the order of tens to hundreds of megatonnes of negative emissions within 300 km of the coast. We conclude that near-coastal OAE has the potential to scale globally to several GtCO2/yr of drawdown with conservative pH constraints, if the effort is spread over the majority of available coastlines. Depending on the location, we find a diverse set of equilibration kinetics, determined by the interplay of gas exchange and surface residence time. Most locations reach an uptake-efficiency plateau of 0.6–0.8mol CO2 per mol of alkalinity after 3–4 years, after which there is little further CO2 uptake. The most ideal locations, reaching an uptake of around 0.8 include north Madagascar, San Francisco, Brazil, Peru and locations close to the southern ocean such as Tasmania, Kerguelen and Patagonia, where the gas exchange appears to occur faster than the surface residence time. Some locations (e.g. Hawaii) take significantly longer to equilibrate (up to 8–10 years), though can still eventually achieve high uptake. If the alkalinity released advects into regions of significant downwelling (e.g. around Iceland) up to half of the OAE potential can be lost to bottom waters. [ABSTRACT FROM AUTHOR]

Tropical climate-smart agriculture could be a cost-effective and scalable nature-based solution toward achieving net-zero greenhouse gas (GHG) emissions in the coming decades. Nevertheless, the lack of integrated on-farm CO 2 , CH 4 , and N 2 O flux measurements remains a barrier to including these systems in certification programs and the carbon (C) market. This systematic literature review critically examines field-measured GHG emission studies within climate-smart agri-systems in Brazil, aiming to: (i) integrate GHG-measured data, (ii) explore geographical representativeness and connections between organizations and authors, (iii) analyze distributions of studied GHG molecules, climate-smart system types, and productive components, (iv) conduct a meta-analysis on the adoption of climate-smart agriculture, and (v) identify methodological and scope gaps, providing insights for future research directions. The systems considered include no-till, well-managed pasture, integrated crop-livestock, and integration with trees (i.e., crop-forestry, livestock-forestry, crop-livestock-forestry, and multistrata agroforestry). Out of 1200 papers mentioning GHGs and climate-smart systems, 74 contained reliable on-farm flux measurements. Most authors were Brazilians affiliated with Embrapa and public Universities. Studies concentrated on the Atlantic Forest and Cerrado, with scarce data for other biomes. Over half of the trials assessed individual GHG molecules and only one climate-smart system. Urochloa spp. and Avena spp. were the most studied forage genera, while soybeans and corn dominated annual crops. Eucalyptus spp. and beef cattle were common trees and animals. No-till, integrated crop-livestock, and agricultural integrations involving trees showed soil C–CH 4 influx from 0.8 to 1.0 kg ha−1 y−1. Transitioning from pasture monoculture to integrated systems decreased N–N 2 O emissions by up to 1.63 kg ha−1 y−1. Converting extensive grazed land to intensified-integrated systems reduced animal CH 4 intensity, with cuts of up to 122 g CH 4 per kg of average daily weight gain. Future research must urgently address methodological issues, such as de-standardization (e.g., 8–10 flux units found per GHG molecule) and the absence of crucial ancillary variables. In conclusion, adopting diversified climate-smart agri-systems shows potential to mitigate GHG emissions, but caution is advised when extrapolating our numerical findings due to limited data across Brazilian edaphoclimatic conditions. We urge scientists to prioritize frequent on-farm measurements of all three GHGs (CO 2 , N 2 O, and CH 4) along with agroecosystem C sequestration across multiple climate-smart systems, enabling reliable and comparable net GHG flux calculations to identify the most sustainable option. Advancing and standardizing GHG measurements in Brazil offer an opportunity to enhance GHGs inventory accuracy, calibrate models, and promote policies and investments that expand refined tropical climate-smart agriculture. [Display omitted] • We systematically reviewed GHG measurements in Brazilian climate-smart agri-systems. • Well-managed pastures, no-till, and integration-based systems mitigate GHG emissions. • Brazilian GHG dataset incompletely represents systems and environmental complexities. • Producing agri-GHG field data is still vital for policies, investments, and C market. • Future GHG research should standardize flux units and include ancillary variables. [ABSTRACT FROM AUTHOR]

Policies for reducing the environmental impact of light-duty vehicles are restarting in Brazil. While electrification attracts more engagement than other forms of carbon footprint reduction, the use of ethanol could achieve faster gains with the existing infrastructure. The prominence of entry-level cars has reduced, which may be due to several factors, making these vehicles uneconomical for manufacturers to produce. This situation is different from those in other countries. It is our premise that other modes, such as walking, cycling, and public transportation, are the main methods of decarbonization. However, most need improvements in terms of security and attractiveness for consumers. Hence, the internal combustion engine will dominate the Brazilian fleet for quite some time. This article discusses the policies used to incentivize the implementation of entry-level vehicles in contrast with electric vehicles based on regression models of the Brazilian fleet. By providing a history of the 1.0 L engine in Brazil, this article debates replacing the indirect displacement taxation with direct CO2 taxation, which can make the Brazilian entry-level car practical again, with the possibility of adopting some incentives. This logic will cause a fleet renovation and more rational energy use. The distinguishing feature of this article is the proposition of possible public policies based on a regression model of the national fleet. The key findings show that the fleet is getting older and heavier, consuming more energy, and emitting greater amounts of CO2 per unit of displacement, for example, 1.0 L. Furthermore, the carbon footprint of the electricity mix is similar to that of the produced ethanol (from well to wheel, the carbon footprint is the same). This highlights the necessity for national policy adjustments and effective public policies to reduce carbon emissions from the energy sector for small vehicles. [ABSTRACT FROM AUTHOR]

Understanding igneous rock emplacement is crucial for deciphering any sedimentary basin's evolution. Its occurrence can be a determining factor for elements of the petroleum system, such as hydrocarbon generation, migration, trap formation, and reservoir quality. The high-impedance nature of igneous rocks in relation to their surrounding host rocks renders amplitude anomaly-based attributes sufficient for the identification of igneous bodies within siliciclastic sequences. However, this is not necessarily valid in pre-salt settings because of the high-impedance carbonates that make the impedance contrast subtle. Furthermore, if the emplacement characterization of the various magmatic pulses that occur in a given area over geological time were better evaluated, it would be possible to assess the gases (such as CO 2) they produce with higher reliability. In this paper, the principal geometric and petroelastic characteristics of the igneous rocks of the Mero Field are described in detail in order to estimate the thermogenic production of CO 2. Both manual and semi-automatic seismic interpretation were carried out to quantitatively and properly reduce the uncertainties inherent to the seismic mapping of these rocks. Thus, a 3D probabilistic igneous facies classification was performed based on a Bayesian inference using the P- and S-impedance well log data available and seismic elastic inversion volumes. These volumes of occurrence probability were useful for semi-automatically extracting maps and geobodies, which, along with conventional manual seismic interpretation, provided hypothetical volumetric scenarios for Mero igneous rocks and also for CO 2 production. Five main intrusive features were recognized based on mainly in seismic geometries found in the Mero Field, two of them being Lower Cretaceous rift-related magmatism synchronous with the pre-salt reservoir deposition and the other three being related to the Santonian/Campanian magmatism. The analyzed data suggests that deep intrusions were responsible for the installation of a multiple hydrothermal vent system in the Santos Basin. During pre-salt sedimentation in the Lower Cretaceous, the emplacement of tholeiitic sills, primarily in low-energy facies at structural depressions, may have played a significant role in the thermal alteration of the sedimentary framework and would have released a significant amount of CO 2 into the atmosphere. It's possible that the reactivation and reuse of these older structures (i.e., sill-related hydrothermal vent complexes generated by tholeiitic intrusions) during alkaline Santonian/Campanian magmatism might have contributed further to the production of additional carbon dioxide, which would be trapped in pre-salt reservoirs in this instance. • Petroelastic and seismic characterization of Santos Basin pre-salt igneous rocks of different ages and compositions. • Characterization of Pre-Salt hydrothermal vents. • Hydrothermal vents as triggers for Pre-Salt CO 2. • CO 2 generation estimates related to intrusions. [ABSTRACT FROM AUTHOR]

The Legal Amazon of Brazil holds vast mangrove forests, but a lack of awareness of their value has prevented their inclusion into results-based payments established by the United Nations Framework Convention on Climate Change. Based on an inventory from over 190 forest plots in Amazon mangroves, we estimate total ecosystem carbon stocks of 468 ± 67 Megagrams (Mg) ha−1; which are significantly higher than Brazilian upland biomes currently included into national carbon offset financing. Conversion of mangroves results in potential emissions of 1228 Mg CO2e ha−1, which are 3-fold higher than land use emissions from conversion of the Amazon rainforest. Our work provides the foundation for the inclusion of mangroves in Brazil's intended Nationally Determined Contribution, and here we show that halting mangrove deforestation in the Legal Amazon would generate avoided emissions of 0.9 ± 0.3 Teragrams (Tg) CO2e yr−1; which is equivalent to the annual carbon accumulation in 82,400 ha of secondary forests. A new study shows that deforestation of Amazon mangroves releases up to four times more carbon dioxide when compared to emissions arising from terrestrial biomes. This study set a foundation for the use of mangroves in Brazil's international policy agreements. [ABSTRACT FROM AUTHOR]

This work aims to assess whether there is a convergence in the emission of Greenhouse Gases (GHG) in the states of Brazil. To achieve this objective, the Phillips and Sul (2007) time series methodology was employed, testing the hypothesis of global (or common) convergence, using data from the Greenhouse Gas Emissions and Removal Estimation System (Sistema de Estimativas de Emissões e Remoções de Gases do Efeito Estufa - SEEG), for the period of 1989–2018, which provides the emission, in tons, of Carbon Monoxide (CO) in agriculture and livestock, as well as of Carbon Dioxide (CO2), for changes in land and forest use. Among the main results, the formation of different convergence clubs is suggested, rejecting the hypothesis of global convergence, and thus presenting four convergence clubs for the CO pollutant and three clubs for the CO2, with two divergent states. When analysing the convergence clubs, it was found that there was a significant reduction in CO emissions in all clubs, and while analysing the CO2, only two of the clubs, which were clubs 3 and 4, managed to reduce their emissions. [ABSTRACT FROM AUTHOR]

This review investigates the effects of the Brazilian agriculture production and forestry sector on carbon dioxide (CO2) emissions. Residual biomasses produced mainly in the agro-industrial and forestry sector as well as fast-growing plants were studied. Possibilities to minimize source-related emissions by sequestering part of carbon in soil and by producing biomass as a substitute for fossil fuel were extensively investigated. The lack of consistency among literature reports on residual biomass makes it difficult to compare CO2 emission reductions between studies and sectors. Data on chemical composition, heating value, proximate and ultimate analysis of the biomasses were collected. Then, the carbon sequestration potential of the biomasses as well as their usability in renewable energy practices were studied. Over 779.6 million tons of agricultural residues were generated in Brazil between 2021 and 2022. This implies a 12.1 million PJ energy potential, while 4.95 million tons of forestry residues was generated in 2019. An estimated carbon content of 276 Tg from these residues could lead to the production of approximately 1014.2 Tg of CO2. Brazilian biomasses, with a particular focus on agro-forest waste, can contribute to the development of sustainable alternative energy sources. Moreover, agro-waste can provide carbon credits for sustainable Brazilian agricultural development. [ABSTRACT FROM AUTHOR]

Statistical properties of turbulence, specifically variances of velocity components, temperature, water vapor, and carbon dioxide densities, are observationally characterized using turbulence measurements carried out between 2009 and 2017, at 25.4 m above surface in a suburban area in the metropolitan region of São Paulo (MRSP), Brazil. An objective analysis indicated that the best method to evaluate the zero-plane displacement (d), among five morphometric and anemometric methods is the temperature variance method. A new procedure based on the convergence of these methods is proposed to estimate the accuracy of the aerodynamic parameters. Normalized standard deviation of wind components and scalar properties are described by similarity functions based on Monin–Obukhov similarity theory. Uncertainties in d and Obukhov length are propagated to similarity functions derived for the MRSP and indicated uncertainties of up to 12% (22%) for wind components, 15% (23%) for temperature, 6% (23%) for water vapor and 11% (23%) for carbon dioxide densities during stable (unstable) conditions. By hypothesis testing it was demonstrated that the coefficients of normalized standard deviations of wind components for neutral stability conditions found at MRSP can be considered statistically equal to Roth's urban averages (Q J R Meteorol Soc126:941–990, 2000), revealing the universal character of these functions. This agreement, added to other evidence, indicates that measurements used in the present study were performed in the inertial sublayer. [ABSTRACT FROM AUTHOR]

Background: The recent studies of the variations in the atmospheric column-averaged CO2 concentration ( X CO 2 ) above croplands and forests show a negative correlation between X CO 2 and Sun Induced Chlorophyll Fluorescence (SIF) and confirmed that photosynthesis is the main regulator of the terrestrial uptake for atmospheric CO2. The remote sensing techniques in this context are very important to observe this relation, however, there is still a time gap in orbital data, since the observation is not daily. Here we analyzed the effects of several variables related to the photosynthetic capacity of vegetation on X CO 2 above São Paulo state during the period from 2015 to 2019 and propose a daily model to estimate the natural changes in atmospheric CO2. Results: The data retrieved from the Orbiting Carbon Observatory-2 (OCO-2), NASA-POWER and Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) show that Global Radiation (Qg), Sun Induced Chlorophyll Fluorescence (SIF) and, Relative Humidity (RH) are the most significant factors for predicting the annual X CO 2 cycle. The daily model of X CO 2 estimated from Qg and RH predicts daily X CO 2 with root mean squared error of 0.47 ppm (the coefficient of determination is equal to 0.44, p < 0.01). Conclusion: The obtained results imply that a significant part of daily X CO 2 variations could be explained by meteorological factors and that further research should be done to quantify the effects of the atmospheric transport and anthropogenic emissions. [ABSTRACT FROM AUTHOR]

The creation of a satellite rapid alert programme (DETER-A) in 2004 was a cornerstone of the Brazilian government's strategy to reduce deforestation. This programme allowed authorities to detect and respond rapidly to periods of deforestation. Due to the fact that the policy instrument was based on multispectral remote radar, weather-related obstacles posed a continuous impediment to the study of deforestation. This paper investigates to what extent cloud cover has reduced the effectiveness of the DETER-A program to detect deforestation. To test this hypothesis, survival model analysis is undertaken on satellite data derived measures of local deforestation. The emphasis is on the state of Maranhão, which is separated into two areas by an arbitrary line of demarcation (Legal Amazon delimitation) where the forest on one side is covered by the satellite monitoring program while the other is not. The results suggest that following the implementation of the satellite monitoring program, there was more deforestation in those years with more cloud persistence in the area covered by the program. Counterfactual simulations indicate that the absence of clouds would have prevented deforestation equivalent to almost 7% of the study region, which is equivalent to 73 million tonnes of CO 2 with a value of US$ 366 million. If the current monitoring system was replaced with the experimental policy instrument DETER-C/DETER INTENSO, cloud cover would be less of an impediment to deforestation detection. • Maranhao in Brazil is divided by an artificial line that separates it in two parts with two different deforestation monitoring policies. • Hence, it provides an ideal setting in which to study the impact of cloud cover on deforestation rates. • When a satellite monitoring programme is in operation, more deforestation occurs during years with greater cloud cover. • Highlights Improved satellite monitoring technologies may have a substantial effect on deforestation rates. [ABSTRACT FROM AUTHOR]

In 2018, the production of hydrogen from fossil fuel feedstocks for industrial use emitted around 830 million tons of carbon dioxide. The development of green hydrogen production from renewable energy is a promising solution to decrease the carbon footprint caused by hydrogen production. Herein, the impact of the variability of the power output simulated from a single‐point irradiance measurement on levelized cost of hydrogen (LCOH) calculations is studied. The analysis is carried out using 7 month of 1 min power and plane‐of‐array irradiance historical data from a 36 MWp photovoltaic (PV) plant located in Brazil. LCOHs calculated using historical power production will be compared with LCOHs calculated using power production simulated by two different methods. The difference between the two methods lies in the extent to which the variability of the power output of the PV plant is considered. The focus is set on off‐grid electrolyzers directly powered by PV solar plants. [ABSTRACT FROM AUTHOR]

• This paper is aimed at the difficult problem of separating apatite from carbonates. • The most common flotation strategy uses inorganic acids. • An effective alternative is the injection of carbon dioxide. • High selectivity was archived using carbon dioxide as apatite depressant. • Injection of carbon dioxide can replace inorganic acids completely. The most common method to concentrate apatite from carbonate phosphate ore is reverse configuration using fatty acids as collectors and inorganic acids as apatite depressants, such as H 2 SO 4 and H 3 PO 4. This work evaluates the process based on the separation between apatite and calcite by flotation, in bench and pilot scale, using carbon dioxide injected through the bubble generation system with the use of saponified coconut fatty acid as a collector, as an alternative to the inorganic acids as apatite depressants in the process circuit developed to treat a uranium-carbonate phosphate ore (Santa Quitéria, Brazil). Moreover, the discharge of natural slimes only was evaluated, without the removal of the grinding slimes, which is not observed in apatite flotation plants for weathered material, where the removal of both kinds of slimes is necessary. The circuit proposed in this study provided significant gains in P 2 O 5 recovery. In calcite flotation studies using carbon dioxide, in RG/CL/RCL mechanical cell circuit configuration, considering the overall performance obtained (grinding product + natural fines), the overall P 2 O 5 recovery was approximately 91% and the P 2 O 5 , SiO 2 and Al 2 O 3 grades were 29%, 11% and 13%, respectively. The results obtained in this study indicated that the process circuit proposed by discharging only natural slimes increases the global P 2 O 5 recovery, and the flotation process based on the injection of carbon dioxide is a potential alternative to concentrate apatite from the Santa Quitéria ore. Furthermore, previous studies have indicated that the use of carbon dioxide instead of inorganic acids as apatite depressants causes less ion accumulation in the process water, which is a major issue mainly in areas with scarce water supply such as the Santa Quitéria region. [ABSTRACT FROM AUTHOR]

• We calibrated the DSSAT/CROPGRO for several soybean maturity groups. • Crop model showed good performance under different tropical conditions. • Water productivity increase can ensure the future growth of soybean yield. • Mean soybean yields increase likely in the future climate due to CO 2 increase. In the next decades, the population is expected to rise by more than two billion people, and the projections of climate change have been considered as one of the greatest future challenges for world food security. Soybean represents more than 60 % of all plant protein produced in the world, and Brazil is the largest world exporter and the second-largest producer. In this paper, we simulated soybean yields for 16 strategically selected agroclimatic zones (CZs) to represent Brazilian production. Experiments conducted throughout the country were used to calibrate the CROPGRO-Soybean model for Brazilian conditions, for the main maturity groups used in Brazil, to simulate current and 40 future climate scenarios, provided by Coupled Model Intercomparison Project 5 (CMIP5) for 2050 in the both 4.5 and 8.5 representative concentration pathways (RCP). We found soybean yield varying by +1 to +32 % across 16 CZs in the average scenario of future climate when compared to the current yields. Yet, we found an increase of about 5% in the yield production risk for RCP 8.5. The main reason for such results was associated with the positive effect of increasing CO 2 on crop water productivity, which overcomes the negative effects of temperature and water stress increases on rainfed Brazilian soybeans. [ABSTRACT FROM AUTHOR]

Soil turning during pre-seeding preparation is meant to loosen and promote physical characteristics responsible for the development of crop roots in soil. In this study, we demonstrate effects of three methods of pre-seeding preparation at two depths of irrigation on carbon dioxide (CO2) efflux as well as the temporal variability in the distribution of soil carbon. This experiment was conducted at the rural cooperative extension research station in Tangará da Serra, Mato Grosso, Brazil, for two wheat production years in 2011 and 2012. The experimental design was randomized in strips, with four repetitions. Wheat was irrigated during the June to early October dry season. The treatments include two methods of soil preparation: traditional preparation with one plowing and two disc harrowings and minimal preparation with one seed bed conditioner pass. A third treatment of direct seeding was also evaluated. Soil CO2 efflux, soil temperature, air-filled soil porosity, and labile carbon were measured. We found soil preparation affects CO2 efflux in irrigated cultivation systems within Brazil's Cerrado savannah, with conventional tillage having greater CO2 emissions than either reduced tillage or direct seeding. Soil CO2 emissions were lower at 508 mm versus 698 mm irrigation depth, but wheat yields were significantly lower. [ABSTRACT FROM AUTHOR]